Large language models for information retrieval: A survey
As a primary means of information acquisition, information retrieval (IR) systems, such as
search engines, have integrated themselves into our daily lives. These systems also serve …
search engines, have integrated themselves into our daily lives. These systems also serve …
Approximate nearest neighbor negative contrastive learning for dense text retrieval
Conducting text retrieval in a dense learned representation space has many intriguing
advantages over sparse retrieval. Yet the effectiveness of dense retrieval (DR) often requires …
advantages over sparse retrieval. Yet the effectiveness of dense retrieval (DR) often requires …
[LIBRO][B] Pretrained transformers for text ranking: Bert and beyond
The goal of text ranking is to generate an ordered list of texts retrieved from a corpus in
response to a query. Although the most common formulation of text ranking is search …
response to a query. Although the most common formulation of text ranking is search …
Utilizing BERT for Information Retrieval: Survey, Applications, Resources, and Challenges
Recent years have witnessed a substantial increase in the use of deep learning to solve
various natural language processing (NLP) problems. Early deep learning models were …
various natural language processing (NLP) problems. Early deep learning models were …
Pretrained transformers for text ranking: BERT and beyond
The goal of text ranking is to generate an ordered list of texts retrieved from a corpus in
response to a query. Although the most common formulation of text ranking is search …
response to a query. Although the most common formulation of text ranking is search …
Pre-training methods in information retrieval
The core of information retrieval (IR) is to identify relevant information from large-scale
resources and return it as a ranked list to respond to user's information need. In recent years …
resources and return it as a ranked list to respond to user's information need. In recent years …
Query expansion by prompting large language models
Query expansion is a widely used technique to improve the recall of search systems. In this
paper, we propose an approach to query expansion that leverages the generative abilities of …
paper, we propose an approach to query expansion that leverages the generative abilities of …
PyTerrier: Declarative experimentation in Python from BM25 to dense retrieval
PyTerrier is a Python-based retrieval framework for expressing simple and complex
information retrieval (IR) pipelines in a declarative manner. While making use of the long …
information retrieval (IR) pipelines in a declarative manner. While making use of the long …
Pseudo-relevance feedback for multiple representation dense retrieval
Pseudo-relevance feedback mechanisms, from Rocchio to the relevance models, have
shown the usefulness of expanding and reweighting the users' initial queries using …
shown the usefulness of expanding and reweighting the users' initial queries using …
ColBERT-PRF: Semantic pseudo-relevance feedback for dense passage and document retrieval
Pseudo-relevance feedback mechanisms, from Rocchio to the relevance models, have
shown the usefulness of expanding and reweighting the users' initial queries using …
shown the usefulness of expanding and reweighting the users' initial queries using …